Since manually annotating new collections of images is expensive and requires great human effort, it is unfeasible to label new target data every time to supervise the model to acquire knowledge from the test domain.
A recently promising approach is to gather data from virtual world environments that mimic as much as possible all the characteristics of the real-world scenarios and where the annotations can be acquired with an automated process. To this end, in this chapter, we introduce viped, a new synthetic dataset generated with the highly photo-realistic graphical engine of the video game GTA V (Grand Theft Auto V) by Rockstar North, that extends the jta dataset presented in [1]}. viped is the first synthetic dataset suitable for the pedestrian detection task, annotated with bounding boxes locating the instances of the people present in the scenes.
